Three Ways to Deal with Uncertainty and Risk in Buying Decisions

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When buyers make a choice, especially about a high-value purchase, they balance three considerations: cost, benefit and risk. What will it cost me to buy this or do this? How will I benefit or what will I get in return? What risks am I taking?

As the author of Bottom-Line Selling, I know how effective ROI calculations can be in driving buying decisions, but even I have to acknowledge that, of those three questions, risk is by far the quirkiest and most slippery concept to get a grasp on psychologically, because there are so many factors at play, many of which simply can’t be precisely defined or measured.

At the risk of stating the obvious, every decision carries a risk, so if you want to sell a product or convince someone to approve an idea of yours, you need to understand how to deal with it, and even how to use the psychology of risk in your favor. Let’s examine how they think and feel about risk, how that affects the choices they make, and how that affects your approach to selling them on your idea or solution.

Why uncertainty is complicated

To be perfectly precise, risk is not the problem—uncertainty is. What’s the difference? Risk is generally known and quantifiable. It may be exact, as in a game of chance, or it may be inexact but reasonably well-known, such as by looking at historical performance. Uncertainty is about not knowing the odds, such as a completely new technology for which there is no known market. Most buying decisions contain some of each.

Even when the risks are exactly quantifiable, people may differ in how they interpret those risks. Some may have a higher appetite for risk because of their personality, or because their situation dictates it. When you’re playing with house money, you may be willing to take larger risks, or you may also may be willing to take larger risks at the opposite end, when you are completely desperate. Where you are in the corporate hierarchy may play a part: what may be a career-limiting wrong decision to a low-level buyer may be a rounding error to a senior-level decision maker.

And that’s when the risks are fairly well quantified. Imagine how much more difficult it becomes when you cross the line from risk to uncertainty. The human mind is not built to calculate the optimum risk/reward choice, even when it has complete information, which it almost never does. So buyers take shortcuts when they evaluate risk and uncertainty, and when you understand those shortcuts, you can jump ahead of them and use them to increase your chances of winning the sale—lower your risk of loss, in other words.

Some psychology – mental shortcuts that buyers take

There is so much more to the psychology of risk than I can cover in one post, but here are three of the most important.

Gain/loss framing

Appetite for risk is dependent on how the decision is framed. According to prospect theory, people are more willing to incur risk to avoid a loss than to reap a gain. For example, most people will not voluntarily accept a one-time coin flip in which they stand to lose as much as they can gain. Potentially losing $100 feels worse than the happiness of winning $100 on an even bet, so most people impose a ”loss aversion ratio” between 1.5 and 2.5.[1] That’s why you may need to spend less time touting your benefits and more effort in helping the buyer realize what they stand to lose if they don’t buy your solution.

In other words, don’t downplay risk, reverse the risk. Get them to think about what they may stand to lose if they go with an alternate choice.

Here’s one example: Suppose your buyer asks you to justify why your price is higher. The standard response is to answer their question directly, by explaining your differentiators and connecting them to benefits; in other words, by telling them what they get for the higher price. That may work, if your benefits are quantifiably better than the price differential, but because of prospect theory, you’re probably going to have to show them at least $2 in benefit for every $1 in price difference. (It’s probably more than that, because the higher cost is certain, and the expected benefit is never guaranteed.)

So, how do you counteract this tendency? You have to focus their mind on what they might be losing by giving up the promise of quality that a higher price brings. Instead of telling them why your price is justified, ask them why the competitor’s price is justified. In a free market, companies charge what the market is wiling to pay, so if they are competing on price, it must be because they know they are not offering the same benefits as higher-priced products. Simply by asking the question, you may get them to shift the focus from the financial risk of a higher price to the potentially greater operational risk of not getting what they need.

Numbers perceived differently depending on how they’re presented

How the numbers are presented has also been shown to affect how the risk is perceived by the decision-maker. Take a hypothetical situation, where your customer faces a problem that results in failures in 30.5% of cases, and is very costly when it happens. You show them historical data that proves that using your solution cuts that down to 26.4% of the time. Is it worth it for the buyer to incur the risk and cost to apply your solution? How would you present the data to improve the chances they will buy?

You could say your solution is 4.1% better.

You could also perfectly honestly say that your solution is 13.4% better. (4.1/30.5 = 13.4%)

When these descriptions were tested with highly educated professional decision makers, 56% chose to try the new  solution when it was presented the first way, and 76% chose to try it when it was presented the second way. That may not sound too surprising, except that in the real world scenario in which the study was done the choices were actually between two medical procedures, the “failure” was patient death, and the decision makers were doctors, whom one would presume would know better. (The literature shows that there is little or no correlation between education and risk assessment.)[2]

Here’s another example: your solution is 99.9% reliable; theirs is 99.8% reliable. You can easily and honestly make a case that yours is twice as reliable! Your solution results in 10 failures per thousand, theirs fails 20 times. If the reliability measure is dropped cell phone calls, that may not be worth paying a premium for, but if it’s a measure of how often a critical machine might fail, it could be huge.[3]

It gets even stranger. The general rule is that the more abstract it is, the less impact, and vice versa. That means that if you want to play down the risks of something, talk about percentages. Next is frequency, or actual numbers: A disease that kills 1,286 out of 10,000 was judged worse than one that kills 24.14% of the population.

So, when describing the risks of competing alternatives, use actual numbers to describe theirs and percentages to describe yours.

Sometimes numbers may actually be irrelevant. It’s called denominator neglect. If you go swimming offshore, you may “know” that your chances of being bitten by a shark could be 1/1,000,000. But you don’t think of the million, you think of the one—because it’s you. On the positive side, I almost never buy lottery tickets, but every time I do, I don’t think of the odds; I envision what life would be like with a few extra million in my bank account. So, if you want to increase the perceived risk of a rare event, get them to imagine what it would be like for it to happen to them.

Imagination plays an important role – either dial it up or dial it down

That’s because imagination easily trumps statistical reasoning. One great example is, imagine a world in which smoking cigarettes was perfectly healthy, except that 1 in a million packs of cigarettes contained a cigarette loaded with dynamite. With 250 million packs sold a day, 250 people would have their heads blown off every single day. You could imagine how quickly the authorities would ban the sale of cigarettes! Yet in real life, cigarettes kill an estimated 3 million people per year worldwide, or more than 30x that, and the only thing we do about it is put warning labels on cigarette packs.[4]

The more easily we can envision something, the more real it seems. One way to make risk more salient in someone’s mind is to get them to imagine the consequences or costs of the risky event actually happening.

A close cousin of vividness is personification—make it personal. Imagine that was someone you know getting the unlucky cigarette. Ads showing a photo of a starving child get more donations than ads providing information about a thousand starving children—even more so than ads that feature both a picture and statistics!

To summarize, dealing with risk may be the most difficult part of your sales messaging, but precisely because it’s the most difficult is why you should pay close attention to it. What if you don’t and your competitor does?

[1] Daniel Kahneman, Thinking, Fast and Slow, p. 284.

[2] Adapted from an actual study reported in Calculated Risks, by Gerd Gigerenzer, p. 203.

[3] See also this example, about cancelled flights.

[4] Adapted from Intuition, by David G. Myers, p. 209.